cv::dilate()是 OpenCV 中用于图像形态学变换的函数之一,与cv::erode()相对,它执行图像的膨胀操作。膨胀是一种将图像中的前景(白色区域)扩展的操作,通常用于填补图像中的小孔洞、连接分离的物体、或增强图像中的亮区域。 1. 函数定义 voidcv::dilate( InputArray src, OutputArray dst, InputArray kernel, Point...
第四个参数也为卷积核锚点;(尚不明确和卷积核锚点冲突有什么后果) 第五个参数为迭代使用dilate()函数的次数,默认为1; 第六个参数为边界填充方式; 第七个参数用于当第六个参数设定为常数时填充的边界值,默认值morphologyDefaultBorderValue(); 腐蚀函数原型: erode( InputArray src, OutputArray dst, InputArray ke...
kernel = np.ones((3, 3), np.uint8)dilated_image = cv2.dilate(binary_image, kernel, iterations=1)eroded_image = cv2.erode(binary_image, kernel, iterations=1)stroke_width_map = dilated_image-eroded_imagestroke_width_mean = np.mean(stroke_width_map)stroke_width_std = np.std(stroke_...
# Harris角点检测 harris_corners = cv2.cornerHarris(gray_image, 2, 3, 0.04) # 归一化和显示结果 harris_corners = cv2.dilate(harris_corners, None) color_image[harris_corners > 0.01 * harris_corners.max()] = [0, 0, 255] cv2.imshow('Harris Corners', color_image) cv2.waitKey(0) cv2....
2。使用OpenCV的角点获取函数 cornerHarries 3。查看识别出的角点 (识别出的角点是一个单元素点,通过 dilate 函数可以扩张这个点,该函数使用一个窗口滑过整个图像,窗口内有任意像素为白色,则窗口变成白色) Python Code import matplotlib.pyplot as plt import numpy as np import cv2 %matplotlib inline # Read in...
dilated_image = cv2.dilate(binary_image, kernel, iterations=1) eroded_image = cv2.erode(binary_image, kernel, iterations=1) stroke_width_map = dilated_image - eroded_image stroke_width_mean = np.mean(stroke_width_map) stroke_width_std = np.std(stroke_width_map) ...
CvInvoke.Dilate(bw, bw, Struct_element, new Point(1,1),3,Emgu.CV.CvEnum.BorderType.Default, new MCvScalar(0, 0, 0)); //腐蚀 当Struct_element模型创建不合理或者膨胀腐蚀次数较大时可能图像会发生偏移 CvInvoke.Erode(bw, bw, Struct_element, new Point(-1, -1), 3,Emgu.CV.CvEnum.Borde...
dilated_image = cv2.dilate(binary_image, kernel, iterations=1) eroded_image = cv2.erode(binary_image, kernel, iterations=1) stroke_width_map = dilated_image - eroded_image stroke_width_mean = np.mean(stroke_width_map) stroke_width_std = np.std(stroke_width_map) ...
dilated_image = cv2.dilate(binary_image, kernel, iterations=1) eroded_image = cv2.erode(binary_image, kernel, iterations=1) stroke_width_map = dilated_image - eroded_image stroke_width_mean = np.mean(stroke_width_map) stroke_widt...
dilated_image = cv2.dilate(image, kernel) 六、图像的轮廓检测 OpenCV提供了cv2.findContours()函数用于检测图像中的轮廓。以下是一个简单的轮廓检测例子: # 转换为灰度图像 gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) 应用阈值 _, thresh = cv2.threshold(gray_image, 127, 255, cv2.THRESH_BI...